Generally, stereo matching means obtaining an accurate and reliable disparity map by estimating disparity between corresponding points between two images obtained at different viewpoints by using the same method as a method of recognizing a distance of an object through two human eyes.
In addition, a three-dimensional image having depth perception can be recovered by generating a depth map using the above-mentioned disparity map. The stereo matching method may be largely classified into an area-based method and a feature-based method. The feature-based method may be relatively free of several restrictions of the area-based method and may generate a more accurate and robust depth map, but has a limitation in generating a relatively sparse depth map. Therefore, a general stereo matching method may be changed according to applications; however, the area-based method capable of generating a dense depth map throughout the entire image is generally used.
However, the area-based method always needs a calibration process that matches an epi-polar line and needs calculation time longer than the feature-based method because it needs to calculate the depth value for the entire area of an image. In addition, under the assumption satisfying conditions in that a light source is to be a point light source at an infinite distance, an object in a scene is to be a Lambertian surface, and distortions of binocular color senses or features are to be relatively small, the stereo matching is performed.